地球科学进展 ›› 2025, Vol. 40 ›› Issue (1): 15 -20. doi: 10.11867/j.issn.1001-8166.2025.0001

大气海洋 上一篇    下一篇

面向碳中和的气候变化预估与风险研究新框架
张井勇()   
  1. 1.中国科学院大气物理研究所 地球系统数值模拟与应用全国重点实验室,北京 100029
    2.中国科学院大学 地球与行星科学学院,北京 100049
  • 收稿日期:2024-11-23 修回日期:2024-12-30 出版日期:2025-01-10
  • 基金资助:
    国家重点研发计划项目(2018YFA0606500);国家重大科技基础设施项目(2023-EL-ZD-00068)

New Framework for Studies of Climate Change Projections and Risks Oriented Towards Carbon Neutrality

Jingyong ZHANG()   

  1. 1.National Laboratory of Earth System Numerical Modeling and Application, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
    2.College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2024-11-23 Revised:2024-12-30 Online:2025-01-10 Published:2025-03-24
  • About author:ZHANG Jingyong, research areas include carbon neutrality and climate change, Earth system simulations and climate prediction. E-mail: zjy@mail.iap.ac.cn
  • Supported by:
    National Key Research and Development Program of China(2018YFA0606500);National Large Scientific and Technological Infrastructure Project(2023-EL-ZD-00068)

基于“正排放时期—净零时期—净负时期”的划分方法,建立了面向碳中和的气候变化预估与风险研究新框架。聚焦“一带一路”主要区域,系统开展了SSP1-1.9和SSP1-2.6两种可持续发展路径情景下面向碳中和的未来平均与极端气候变化预估以及灾害风险研究。在全球碳中和时期,预计“一带一路”主要区域平均与极端气候变化将呈现新特征、新格局,气候灾害风险将出现新变化。建立的新框架为气候变化未来预估与灾害风险评估提供了新方案,建议正在启动与开展的联合国政府间气候变化专门委员会第七次气候变化评估报告及将来的气候变化评估报告纳入面向碳中和的气候变化评估作为其重要组成部分,为人类社会共同应对气候变化和实现可持续发展提供新认识。最后,讨论了人工智能技术在未来气候变化预估与风险评估中的应用。

A new framework for studying climate change projections and disaster risks oriented towards carbon neutrality was developed using a division method of positive emissions, net zero, and net negative periods. Focusing on the main Belt and Road regions, future mean and extreme climate change projections and disaster risks oriented towards carbon neutrality were systematically addressed under the SSP1-1.9 and SSP1-2.6 sustainable development pathways. Moreover, it is projected that over global carbon neutrality or net-zero periods, climate change will exhibit new characteristics and patterns, and disaster risks will undergo new changes over the main Belt and Road regions. The newly developed framework provides a new scheme for climate change projection and disaster risk assessment. The seventh assessment report of the Intergovernmental Panel on Climate Change and other future assessment reports on climate change should include climate change projections and disaster risk assessments oriented towards carbon neutrality, which can provide new scientific knowledge for jointly dealing with climate change and achieving sustainable development. Additionally, the role and application of Artificial Intelligence in future climate change projections and climate disaster risks assessments are discussed.

中图分类号: 

图1 “正排放时期—净零时期—净负时期”的划分方法概念图
Fig. 1 Conceptual diagram of the division method for “Positive Emission Period-Net Zero Period-Net Negative Period”
图2 “不同未来时期—不同温升目标—面向碳中和目标”的未来气候变化预估与风险评估演进过程
Fig. 2 The evolution process of climate change projections and risks assessment for “Different Future Periods-Different Temperature Rise Targets-Towards Carbon Neutrality Goals”
图3 人工智能在未来气候变化预估与风险评估中的作用
Fig. 3 The role and application of artificial intelligence in future climate change projections and risks assessment
1 Core Writing Team, LEE H, ROMERO J. Summary for policymakers[C]// Climate change 2023: synthesis report. contribution of working groups I, II and III to the sixth assessment report of the intergovernmental panel on climate change. Geneva, Switzerland, 2023: 1-34.
2 Panel for the Fourth National Assessment Report on Climate Change. Fourth national assessment report on climate change [M]. Beijing: Science Press, 2022.
《第四次气候变化国家评估报告》编写委员会. 第四次气候变化国家评估报告 [M]. 北京:科学出版社, 2022.
3 ELSNER M, ATKINSON G, ZAHIDI S. The global risks report 2025 [R]. Swit zerland: World Economic Forum, 2025.
4 HE J K, LI Z, ZHANG X L, et al. Towards carbon neutrality: a study on China’s long-term low-carbon transition pathways and strategies[J]. Environmental Science and Ecotechnology2022, 9. DOI:10.1016/j.ese.2021.100134 .
5 DING Zhongli, ZHANG Tao. Carbon neutralization: logical system and technical requirements[M]. Beijing: Science Press, 2022.
丁仲礼, 张涛. 碳中和逻辑体系与技术需求[M]. 北京: 科学出版社, 2022.
6 UNEP (United Nations Environment Programme). Emissions gap report 2022: the closing window—climate crisis calls for rapid transformation of societies—executive summary [C/OL]. Nairobi, 2022. [2024-10-20]. .
7 WANG Changlin, CHEN Zhenlin, CHEN Ying, et al. Annual report on actions to address climate change (2024) [M]. Beijing: Social Sciences Academic Press, 2024.
王昌林,陈振林,陈迎,等. 应对气候变化报告(2024) [M]. 北京:社会科学文献出版社,2024.
8 ZHANG Renhe. Scientific issues concerning the carbon neutrality[J]. Climate Change Research202420(6): 661-668.
张人禾. 实现碳中和目标涉及的科学问题[J]. 气候变化研究进展202420(6): 661-668.
9 GARISTO D, KOZLOV M, TOLLEFSON J. What Trump’s flurry of executive orders means for science [J]. Nature2025637: 1 027-1 028.
10 ZHANG Jingyong, ZHUANG Yuanhuang, ZHANG Jianping, et al. Projections of future mean and extreme climate changes over the BRI regions under the carbon neutrality target[M]. Beijing: China Meteorological Press, 2021.
张井勇, 庄园煌, 张建平, 等. 碳中和目标下“一带一路”未来平均与极端气候变化预估[M]. 北京: 气象出版社, 2021.
11 ZHANG J Y, CHEN F. Future projections of daily maximum and minimum temperatures over East Asia for the carbon neutrality period of 2050-2060[J]. Theoretical and Applied Climatology2022150(1): 203-213.
12 ZHANG Jingyong, HE Jing, ZHANG Lixia, et al. Main climate change characteristics and disaster risks oriented towards carbon neutrality over the Belt and Road regions[J]. Bulletin of Chinese Academy of Sciences202338(9): 1 371-1 386.
张井勇, 何静, 张丽霞, 等. 面向碳中和的“一带一路”气候变化主要特征与灾害风险研究[J]. 中国科学院院刊202338(9): 1 371-1 386.
13 HE J, ZHANG J Y, DONG W J, et al. Projected changes in SWA over the main BRI regions for net-zero and net-negative future[J]. Ecosystem Health and Sustainability2024, 10. DOI:10.34133/ehs.0145 .
14 REICHSTEIN M, CAMPS-VALLS G, STEVENS B, et al. Deep learning and process understanding for data-driven Earth system science[J]. Nature2019566(7 743): 195-204.
15 SCHNEIDER T, BEHERA S, BOCCALETTI G, et al. Harnessing AI and computing to advance climate modelling and prediction[J]. Nature Climate Change202313: 887-889.
16 CHEN M, QIAN Z, BOERS N, et al. Collaboration between artificial intelligence and Earth science communities for mutual benefit[J]. Nature Geoscience202417: 949-952.
17 KOCHKOV D, YUVAL J, LANGMORE I, et al. Neural general circulation models for weather and climate[J]. Nature2024632(8 027): 1 060-1 066.
18 VANCE T C, HUANG T, BUTLER K A. Big data in Earth science: emerging practice and promise[J]. Science2024383(6 688). DOI: 10.1126/science.adh9607 .
19 WONG C. How AI is improving climate forecasts[J]. Nature2024628(8 009): 710-712.
20 CHEN Deliang, TAN Xianchun, PENG Zhe, et al. Opportunities and challenges of artificial intelligence in climate research and services[J]. Climate Change Research202420(6): 669-681.
陈德亮, 谭显春, 彭喆, 等. 人工智能在气候研究和服务中的机遇与挑战[J]. 气候变化研究进展202420(6): 669-681.
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